Head of Data Operations

Diligenta
Peterborough
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead - AWS & Snowflake

Head of Data Science and Architecture

Head of Underwriting Quality

Senior Analyst & Data Specialist

Senior Data Analyst

Head of Retail Transformation – Data Science and Reporting

Head of Data Operations

Salary:From £88086-£110107

Who are Diligenta

Diligenta's vision is to be acknowledged as Best in-class Platform based Life and Pensions Administration Service provider. Customer service is at the heart of everything we do and our aim is to transform our clients' operations. A business that has been described as 'home' by existing employees, we drive a culture that is founded on positive change and development.

Summary of the role

Delivering excellent customer journeys is core to Diligenta's strategy and due to continued growth and the evolution of our core platform a centralised data strategy and organisation is essential to support the business going forward as it continues to grow.

In this newly created role you will be responsible for the creation and leadership of this new centralised team.

What you'll be doing

Are you are looking for a new opportunity that allows you to create a data capability from scratch, recruit and lead a team and be responsible for leading on data strategy and operations? If so then look no further.

We are looking for an experienced data leader, someone who has experienced the ups and downs of creating a data capability previously. Coming from a background of data architecture and data science you will define, create and lead a centralised data function who be responsible for safeguarding and governing data ingestion, storage and consumption moving forward.

In your role you will be responsible for developing and implementing a data strategy to align with business goals. You will also be responsible for leading data operations, defining and implementing data governance policies, procedures and standards and ensuring data security, privacy and compliance with FCA regulations.

Other responsibilities include;

Build and manage a high-performing data operations team of data architects, data engineers and data scientists. Evaluate and select appropriate data storage, management and analytics tools and be responsible for their governance. Build a new data lake along with relevant security and governance requirements. Drive data-driven decision making and data-driven culture throughout the business. Optimise data infrastructure for current and future performance, scalability and security.

What we're looking for

To be successful in this role we are looking for an experienced data leader, someone who has built and owned a strategy and operation from the ground up driving business value. You will;

Have a strong understanding of data governance, data security and data privacy. Have excellent knowledge of data architecture and data management tools. Have a background in leading data operations previously including (but not limited to) architects, data scientists and data engineers. Financial Services experience is desirable but not essential.

Benefits

Benefits

33 days including Bank Holidays Eligibility for an annual discretionary bonus scheme Car Allowance (£5,000) Private Healthcare Personal and career development opportunities to progress your aspirations within the company as well as through our global parent company (Tata Consultancy Services) Access to Perks at Work (an online discounted shopping platform) saving you money on a wide range of goods and services, including your weekly food shop, holidays and electrical goods Cycle to Work Scheme & Interest free Season Ticket loans A companywide Wellbeing programme, including an Employee Assistance Programme and other benefits/resources to support your mental/physical and financial wellbeing A comprehensive set of Moments that Matter policies, such as Carer's Leave, Foster Leave and Retirement Leave A contributory company pension scheme where we match your contributions up to 6%, Group Life Assurance ('Death in Service") & Group Income Protection Apply to find out about our other benefits

Get in touch

This is a fantastic opportunity, one that doesn't often present itself, to build and create a brand new, centralised, data capability. You will have the remit and ability to build something amazing, as you see fit, and be able to witness first-hand the value you, your team and your work will deliver to the business and its customers.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.